Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.
#8 best model for Semantic Segmentation on Cityscapes val
In this paper, to relieve the overfitting effect of ResNet and its improvements (i. e., Wide ResNet, PyramidNet, and ResNeXt), we propose a new regularization method called ShakeDrop regularization.
We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution).
#52 best model for Image Classification on ImageNet
We propose a novel approach for instance-level image retrieval.
#3 best model for Image Retrieval on Oxf5k
In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications.
#9 best model for Conditional Image Generation on CIFAR-10
We present MorphNet, an approach to automate the design of neural network structures.
The approach combines, in a black-box fashion, multiple models trained with disjoint datasets, such as records from different subsets of users.
Deep learning frameworks have often focused on either usability or speed, but not both.
This tutorial will introduce the Computational Network Toolkit, or CNTK, Microsoft's cutting-edge open-source deep-learning toolkit for Windows and Linux.